The Agentic AI
Hardware Firewall.
Hardware-enforced safety for autonomous intelligence.
A dedicated co-processor on separate silicon that formally verifies every AI action and physically severs the circuit if a safety rule is violated.
Software guardrails share the same memory as the AI they police.
They can be bypassed. Published research proves universal adversarial attacks defeat every aligned model.
The result is rarely an incident. It's a deployment that never happens, because nobody can prove which agent acted, on whose authority, or why it was permitted.
For autonomous systems in robotics, finance and critical infrastructure,
"Usually safe" is not safe enough.
Software safety is probabilistic. It works most of the time.Evrmind safety is deterministic. It works every time.
The Regulatory Clock Is Ticking
EU AI Act. Transparency obligations apply from 2 August 2026.
- •High-risk obligations deferred to 2 December 2027 and 2 August 2028 under the Digital Omnibus, approved 29 June 2026, because the compliance infrastructure was not ready in time.
- •Mandatory conformity assessments, risk management systems and incident reporting for high-risk AI systems.
- •DORA requires financial institutions to evidence operational resilience across their ICT estate, including systems they do not operate themselves.
- •Penalties up to €35 million or 7% of global turnover.
Boards must now declare their controls effective, not merely present.
- •FRC Provision 29 of the UK Corporate Governance Code applies to financial years beginning on or after 1 January 2026. Boards must declare the effectiveness of material controls, now including operational controls, on a comply or explain basis.
- •FCA Consumer Duty requires firms to evidence good outcomes, not documented intentions.
- •Sector regulators are already enforcing within existing powers: FCA, ICO and MHRA.
- •The AI Security Institute conducts safety evaluations on frontier systems.
State frameworks are being rewritten, not withdrawn.
- •Colorado repealed and replaced its AI Act in May 2026 with a narrower automated decision-making disclosure regime, effective 1 January 2027.
- •Impact assessments, transparency disclosures and consumer protections are required across multiple states.
- •The White House National Policy Framework for AI was published on 20 March 2026.
Deadlines move. The requirement doesn't. A policy is a statement of intent; Evrmind produces the evidence, cryptographic proof of every AI decision, generated in hardware, independent of the system being governed.
Safety That Cannot Be Bypassed
A dedicated safety co-processor on separate silicon. Every proposed action is formally verified against the loaded rules, a signed record is produced, and a physical gate blocks anything that fails. Deterministic, not probabilistic.
Separate Silicon
Enforcement lives outside the AI's trust domain. The AI cannot reprogram, bypass or access it. It holds when the link is lost and when the software stack is compromised.
Deterministic by Design
Every action is verified by formal proof before it can execute. Default state is deny. Fail state is safe.
One Constitution
Safety rules are written once and compiled to hardware-enforced logic. Robotics limits, airspace rules, clinical constraints. Same chip, different rules, updated through authenticated provisioning.
The signal path.
The PAGE pipeline: Proof, Attest, Govern, Enforce.
PROOF
Formal Proof EngineMathematical proof of constitutional compliance. Every AI action is formally verified against a loaded set of rules before it can execute.
ATTEST
Cryptographic RecordA signed, tamper-evident record of every decision, generated in hardware. Any auditor, regulator or partner can verify the system obeyed its rules without access to the AI or its data.
GOVERN
Constitutional RulesLoadable constitutional rules for any industry. Robotics safety, financial compliance, surgical constraints, infrastructure limits. Same chip, different rules.
ENFORCE
Physical InterdictionPhysics-based enforcement on separate silicon. The AI cannot reprogram, bypass, or access the safety processor. If the proof fails, the circuit stays open.
Verifiable Progress
Gate-level interdiction demonstrated on Xilinx Zynq 7020 FPGA at 80ns
Full deterministic AI stack from formal verification to hardware enforcement (UKIPO)
Substrate-Invariant Safety, Topological Regularisation, and Thermodynamic Synthesis (Zenodo)
Signed with an ESA-backed satellite communications operator (hardware in orbit)
OGEL and GEA export licences secured.
How it works, in two stages.
Watch it enforce.
Hardware Safety Layer. TRL 6 on Physical Silicon
The same safety rules compiled to a dedicated co-processor on separate silicon. Gate-level interdiction on Xilinx Zynq 7020 FPGA. The AI cannot reprogram, bypass, or access the safety processor. If the proof fails, the circuit stays open.
Keep the record.
Decision Record. A Signed Proof of Every Verdict
What the operator sees. Every proposed action, its verdict, and a signed, tamper-evident proof of the decision. This demonstration runs the verification engine in software through EvrGuard; on the chip, the same record is generated in hardware.
Built for High-Stakes Domains
ROBOTICS AND INDUSTRIAL AUTOMATION
Collaborative robots, warehouse automation and industrial control. Force, speed and proximity limits are verified in hardware before the actuator moves, independent of the controller that proposed the motion.
Outcome: Robots working alongside people, with a safety case that does not depend on the controller behaving.
AUTOMOTIVE AND AUTONOMOUS VEHICLES
The automotive industry already accepts that safety belongs on separate silicon: lockstep cores, safety islands, ASIL-rated parts. Those answer whether the hardware is working. Evrmind answers whether the action is permitted.
Outcome: A familiar pattern applied one layer up, from component integrity to decision authority.
DRONES AND UNCREWED SYSTEMS
Airspace rules, geofences and operational envelopes enforced on the aircraft, from independent position and state data rather than the autonomy's own interpretation. Enforcement holds when the link does not.
Outcome: Beyond visual line of sight operations backed by evidence a regulator can verify.
AGENTIC AI FOR ENTERPRISE
Coding assistants, DevOps agents and autonomous workflows holding real credentials and real system access. Every action is checked against its authority before it executes.
Outcome: Agents given the access that makes them useful, because you can prove where the boundary is.
FINANCE AND BANKING
Autonomous execution, payments and risk decisions at machine speed. Every action carries a cryptographic record of what was checked and on whose authority, generated in hardware.
Outcome: The audit evidence exists before anyone asks for it.
MEDICAL AND CLINICAL AI
Surgical robotics, dosing and clinical decision support. If a proposed action falls outside the loaded patient safety parameters, the output is held at logic zero and the action does not reach the patient.
Outcome: Clinical safety that can be certified rather than trusted.
CRITICAL INFRASTRUCTURE AND ENERGY
Grid switching, load balancing and control decisions where a single incorrect action cascades. Safety and regulatory limits are enforced between the control AI and the plant.
Outcome: Autonomy in the control room that the safety case can actually accommodate.
SPACE AND SATELLITE AUTONOMY
Orbital manoeuvres, collision avoidance and payload operations decided on board, where ground confirmation may be minutes away or unavailable. Mission rules are enforced at the point of action, regardless of the state of the link.
Outcome: Autonomy in orbit that stays inside its mission envelope, with a signed record for ground review.
FAQs
01What is hardware-enforced AI safety?
Safety rules enforced by a physical circuit rather than by software. A dedicated co-processor verifies every action an AI proposes and blocks anything that violates the loaded rules. Because the enforcement is separate silicon, the AI cannot reprogram or bypass it.
02Why are software guardrails not enough?
Software guardrails share the same memory and processor as the AI they police, so a compromised or jailbroken system can bypass them. Published research demonstrates universal adversarial attacks that defeat every aligned model. Hardware enforcement sits outside the AI's trust domain.
03What is an AI safety co-processor?
A separate chip placed between an AI system and its actuators. Evrmind's co-processor formally verifies each proposed action, produces a signed record of the decision, and physically gates the output. Default state is deny. Fail state is safe.
04How fast is hardware interdiction?
80 nanoseconds, measured on a Xilinx Zynq 7020 FPGA. Verification happens between an AI proposing an action and the actuator receiving it, with no meaningful latency added to the system.
05Does it require changes to the AI model?
No. The co-processor sits in the actuation path and works with any autonomy stack. No retraining, no modification to the AI, no recompiled software on the host.
06What evidence does it produce for regulators and auditors?
A signed, tamper-evident record of every decision, generated in hardware. An auditor, regulator or partner can verify the system obeyed its rules without access to the AI or its data.
Two Products. One Architecture.
Choose the deployment model that fits your requirements.
EVRCHIP
Hardware DeploymentPhysics-based enforcement on separate silicon. For autonomous systems where AI directly controls physical actuators. The wire does not connect until the mathematics proves safe.
EVRGUARD
Cloud DeploymentDeterministic mathematical verification as a service. The same engine that powers our chip, deployed as a cloud API. No model to jailbreak. No weights to poison. For enterprises where software controls execution.
Ready for hardware-enforced AI safety?
Deterministic enforcement for the systems where it matters most.